Leveraging Machine Learning and Genomics in Target Identification and Validation to Tackle Complex Disease Mechanisms
26 Sep 2024
Target Identification
- What are some key considerations for implementing machine learning algorithms to handle diverse molecular profiles and multiple disease subtypes?
- How can leveraging genomic data that can stratify patient populations or uncover molecular signatures inform target identification and validation strategies?
- How can collaborations between data scientists, computational biologists, translational scientists, and clinicians increase robustness and translational potential of the target identification and validation process?
- What strategies can be used to validate machine learning driven target predictions in preclinical models and clinical trials?
- What are some of the main limitations of as well as future directions for integration of machine learning and genomics into target identification and validation?
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